Gray Swan

“So far, we are still a lot, in a lot of cases, operating on the condition that your agent has your permissions. Yeah. That is a very standard default. And I think that will be changed. I mean, your permissions may be in a sandbox, but still kind of your permis…”

“I think in terms of how this will evolve, actually, I don't think it'll be per app, but I think what will happen first is people have different personas that they have, right? So you don't want your work life and your home email to be mixed up. Yeah. Right. A …”

“One of the bigger challenges that people are going to face when they do start to roll out, like these agent identity sort of viewpoints and solutions is you run into that same kind of usability problem. Where like, what's the real recourse? Well, it stopped. I…”

“We know that it has happened and it has caused real damage. That's the factor that's driven some people to us, right? Is they want protection from that.”

“The name gray swan is sort of in reference to black swan events, which are things no one could see coming. A gray swan is an unlikely event that you can kind of see coming. And that's kind of where we are with all of this, right? This is going to happen. We kn…”

“So we just have a bunch of trajectories of actual people using OpenClaw. And tons and tons of different scenarios and just threw shade at it and like found breaks for each and every one of them, right?”

“One of the most effective ways of doing capability elicitation is actually through some amount of what you would call red teaming, right? So if a model refuses a task because it thinks it's being evaluated, but it knows how to complete that task, getting it to…”

“But for a skilled, like, human red teamer, they could fish the human participants, like, with the 60 to 70% success.”

“It's a really great community. Like, 15,000 people come and hang out on the Discord server. Not all of them take part in every competition, but a lot of good data and good signal is provided to, you know, the upstream model developers through, through that com…”

“There were a couple of models that seemed to be very, very robust, right? Like the red teamers found just a handful of successful breaks on them.”

“However, one thing that we are finding, and this is actually, I think we're kind of crossing this point too. Is that in a lot of the latest experiments, we can do much better than people, than human red teamers now at breaking these models. When I say we, I me…”

“Like enterprises are not willing to put up their pre-deployment agents on the arena for the general public to come hit. They're fine if it's, you know, 20 people that, that we've kind of handpicked from the arena.”